Conditioning Variables and the Cross Section of Stock Returns

Previous studies identify predetermined variables that predict stock and bond returns through time. This paper shows that loadings on the same variables provide significant cross-sectional explanatory power for stock portfolio returns. The loadings are significant given the three factors advocated by Fama and French (1993) and the four factors of Elton, Gruber, and Blake (1995). The explanatory power of the loadings on lagged variables is robust to various portfolio grouping procedures and other considerations. The results carry implications for risk analysis, performance measurement, cost-of-capital calculations, and other applications.     

Differences of Opinion and the Cross Section of Stock Returns

We provide evidence that stocks with higher dispersion in analysts' earnings forecasts earn lower future returns than otherwise similar stocks. This effect is most pronounced in small stocks and stocks that have performed poorly over the past year. Interpreting dispersion in analysts' forecasts as a proxy for differences in opinion about a stock, we show that this evidence is consistent with the hypothesis that prices will reflect the optimistic view whenever investors with the lowest valuations do not trade. By contrast, our evidence is inconsistent with a view that dispersion in analysts' forecasts proxies for risk.     

Analyst Forecasts and the Cross Section of European Stock Returns

We examine revisions to earnings forecasts by equity analysts and their role in predicting stock returns. We provide evidence that European stocks with net upward revised forecasts earn higher future returns than otherwise similar stocks. This effect is not concentrated in small stocks, stocks with low analyst coverage, or stocks with low book‐to‐market ratios. We find differences in the return continuation patterns of stocks with upward versus downward revisions, namely, bad news travels quickly, but good news travels slowly. This result is consistent with investors' attaching greater significance to poor earnings forecasts, but adopting a wait‐and‐see approach to good news.     

Investor Attention and Stock Returns: International Evidence

This article examines the asymmetric/discriminative effects of investor attention on expected stock returns among 15 markets through economic expansions and recessions. The predictive power of attention tends to be short-lived and weakens the autocorrelation within returns. Accounting for business cycles not only confirms that the predictability of attention endures with volatility but also explicates the asymmetric effects that underlying pessimism functions better. International evidence contributes to the literature on investor attention and reveals the discrepant effects of attention with three levels of market efficiency: semi-strong, stronger than semi-strong, and weak.     

International Evidence on the Predictability of Stock Returns

This article examines the predictability of stock returns using international stock market data from eighteen countries. The study finds that the ability of dividend yields to predict stock returns increases as the return horizon lengthens from one month to forty-eight months. These results add to earlier ones, based on U.S. data only, showing that predictability grows with the return horizon. The study also explores why the observed pattern of predictability arises and provides evidence supporting the reasons suggested by Fama and French.     

Evidence on the Characteristics of Cross Sectional Variation in Stock Returns

Firm sizes and book-to-market ratios are both highly correlated with the average returns of common stocks. Fama and French (1993) argue that the association between these characteristics and returns arise because the characteristics are proxies for nondiversifiable factor risk. In contrast, the evidence in this article indicates that the return premia on small capitalization and high book-to-market stocks does not arise because of the comovements of these stocks with pervasive factors. It is the characteristics rather than the covariance structure of returns that appear to explain the cross-sectional variation in stock returns.     

The Week-End Effect in Common Stock Returns: The International Evidence

This paper examines the daily stock market returns for four foreign countries. We find a so-called “week-end effect” in each country. In addition, the lowest mean returns for the Japanese and Australian stock markets occur on Tuesday. The remainder of the paper answers four questions. Are seasonal patterns in foreign stock markets independent of those previously reported in the U.S.? Do Japan and Australia exhibit a seasonal one day out of phase due to different time zones? Do settlement procedures across countries bias week-end effects? Does the seasonal pattern in foreign exchange offset the week-end effect in stocks for Americans investing overseas?     

Volatility Spillovers Between Stock Returns and Exchange Rate Changes: International Evidence

We investigate interdependencies between stock returns and exchange rate changes for six industrialised countries, namely the US, the UK, Japan, Germany, France and Canada, by testing for volatility spillovers using a bivariate EGARCH model. Volatility spillovers from stock returns to exchange rate changes are found for all countries except Germany. These spillovers are symmetric in nature. No evidence is found of volatility spillovers from exchange rate changes to stock returns for any country. Spillovers from stock returns to exchange rate changes have increased since October 1987. This finding is consistent with the notion that international financial markets have become increasingly integrated.     

Volatility Clustering, Asymmetry and Hysteresis in Stock Returns: International Evidence

Encompassing a very broad family of ARCH-GARCH models, we show that the AT-GARCH (1,1) model, where volatility rises more in response to bad newsthan to good news, and where news are considered bad only below a certain level, is a remarkably robust representation of worldwide stock market returns. The residual structure is then captured by extending ATGARCH (1,1) to an hysteresis model, HGARCH, where we modelstructured memory effects from past innovations. Obviously, this feature relates to the psychology of the markets and the way traders process information. For the French stock market we show that votalitity is affected differently, depending on the recent past being characterized by returns all above or below a certain level. In the same way a longer term trend may also influence volatility. It is found that bad news are discounted very quickly in volatility, this effect being reinforced when it comes after a negative trend in the stock index. On the opposite, good news have a very small impact on volatility except when they are clustered over a few days, which in this case reduces volatility.     

Industry‐Specific Human Capital,Idiosyncratic Risk,and the Cross‐Section of Expected Stock Returns

Human capital is one of the largest assets in the economy and in theory may play an important role for asset pricing. Human capital is heterogeneous across investors. One source of heterogeneity is industry affiliation. I show that the cross‐section of expected stock returns is primarily affected by industry‐level rather than aggregate labor income risk. Furthermore, when human capital is excluded from the asset pricing model, the resulting idiosyncratic risk may appear to be priced. I find that the premium for idiosyncratic risk documented by several empirical studies depends on the covariance between stock and human capital returns.     

股票横截面收益特性“异常”与行为金融学

面对股票市场横截面收益特性不符合CAPM，理论界有很多观点，其中最活跃和最有发展前途的就是所谓的行为金融学。行为金融学对传统的理性人假设进行了各种形式的放宽，研究非严格理性的投资的行为将对股票市场的特性带来怎样的影响。     

Real Options Models of the Firm,Capacity Overhang,and the Cross Section of Stock Returns

We use a stochastic frontier model to obtain a stock‐level estimate of the difference between a firm's installed production capacity and its optimal capacity. We show that this “capacity overhang” estimate relates significantly negatively to the cross section of stock returns, even when controlling for popular pricing factors. The negative relation persists among small and large stocks, stocks with more or less reversible investments, and in good and bad economic states. Capacity overhang helps explain momentum and profitability anomalies, but not value and investment anomalies. Our evidence supports real options models of the firm featuring valuable divestment options.     

Investment and the Cross‐Section of Equity Returns

The data show that, upon being hit by adverse profitability shocks, large public firms have ample latitude to divest their least productive assets, reducing the risk faced by shareholders and the returns that they are likely to demand. In the one‐factor production‐based asset pricing model, when the frictions to capital adjustment are shaped to respect the evidence on investment, the model‐generated cross‐sectional dispersion of returns is only a small fraction of that documented in the data. Our conclusions hold even when operating or labor leverage is modeled in ways shown to be promising in the extant literature.     

Forecast Dispersion and the Cross Section of Expected Returns

Recent work by Diether, Malloy, and Scherbina (2002) has established a negative relationship between stock returns and the dispersion of analysts' earnings forecasts. I offer a simple explanation for this phenomenon based on the interpretation of dispersion as a proxy for unpriced information risk arising when asset values are unobservable. The relationship then follows from a general options‐pricing result: For a levered firm, expected returns should always decrease with the level of idiosyncratic asset risk. This story is formalized with a straightforward model. Reasonable parameter values produce large effects, and the theory's main empirical prediction is supported in cross‐sectional tests.     

Sparse Signals in the Cross‐Section of Returns

This paper applies the Least Absolute Shrinkage and Selection Operator (LASSO) to make rolling one‐minute‐ahead return forecasts using the entire cross‐section of lagged returns as candidate predictors. The LASSO increases both out‐of‐sample fit and forecast‐implied Sharpe ratios. This out‐of‐sample success comes from identifying predictors that are unexpected, short‐lived, and sparse. Although the LASSO uses a statistical rule rather than economic intuition to identify predictors, the predictors it identifies are nevertheless associated with economically meaningful events: the LASSO tends to identify as predictors stocks with news about fundamentals.     

Value versus Growth: Time‐Varying Expected Stock Returns

Is the value premium predictable? We study time variations of the expected value premium using a two‐state Markov switching model. We find that when conditional volatilities are high, the expected excess returns of value stocks are more sensitive to aggregate economic conditions than the expected excess returns of growth stocks. As a result, the expected value premium is time varying. It spikes upward in the high volatility state, only to decline more gradually in the subsequent periods. However, out‐of‐sample predictability of the value premium is close to nonexistent.     

Intraday Patterns in the Cross‐section of Stock Returns

Motivated by the literature on investment flows and optimal trading, we examine intraday predictability in the cross‐section of stock returns. We find a striking pattern of return continuation at half‐hour intervals that are exact multiples of a trading day, and this effect lasts for at least 40 trading days. Volume, order imbalance, volatility, and bid‐ask spreads exhibit similar patterns, but do not explain the return patterns. We also show that short‐term return reversal is driven by temporary liquidity imbalances lasting less than an hour and bid‐ask bounce. Timing trades can reduce execution costs by the equivalent of the effective spread.